2 * Copyright (c) 2020 Samsung Electronics Co., Ltd. All Rights Reserved
3 * Copyright 2019 The TensorFlow Authors. All Rights Reserved.
5 * Licensed under the Apache License, Version 2.0 (the "License");
6 * you may not use this file except in compliance with the License.
7 * You may obtain a copy of the License at
9 * http://www.apache.org/licenses/LICENSE-2.0
11 * Unless required by applicable law or agreed to in writing, software
12 * distributed under the License is distributed on an "AS IS" BASIS,
13 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 * See the License for the specific language governing permissions and
15 * limitations under the License.
18 #include "kernels/Sub.h"
19 #include "kernels/Utils.h"
23 #include <tensorflow/lite/kernels/internal/reference/process_broadcast_shapes.h>
27 namespace luci_interpreter
32 Sub::Sub(const Tensor *input1, const Tensor *input2, Tensor *output, const SubParams ¶ms)
33 : KernelWithParams<SubParams>({input1, input2}, {output}, params)
39 LUCI_INTERPRETER_CHECK(!(input1()->element_type() != input2()->element_type()))
40 LUCI_INTERPRETER_CHECK(!(input1()->element_type() != output()->element_type()))
41 output()->resize(calculateShapeForBroadcast(input1()->shape(), input2()->shape()));
44 void Sub::execute() const
46 switch (input1()->element_type())
48 case DataType::FLOAT32:
52 evalInteger<int64_t>();
55 evalInteger<int32_t>();
61 throw std::runtime_error("Unsupported type.");
65 void Sub::evalFloat() const
67 tflite::ArithmeticParams params{};
68 fillArithmeticActivationRange<float>(params, _params.activation);
70 const bool need_broadcast = tflite::reference_ops::ProcessBroadcastShapes(
71 getTensorShape(input1()), getTensorShape(input2()), ¶ms);
75 tflite::reference_ops::BroadcastSubSlow(
76 params, getTensorShape(input1()), getTensorData<float>(input1()), getTensorShape(input2()),
77 getTensorData<float>(input2()), getTensorShape(output()), getTensorData<float>(output()));
81 luci_interpreter_pal::Sub(params, getTensorShape(input1()), getTensorData<float>(input1()),
82 getTensorShape(input2()), getTensorData<float>(input2()),
83 getTensorShape(output()), getTensorData<float>(output()));
87 template <typename T> void Sub::evalInteger() const
89 tflite::ArithmeticParams params{};
90 fillArithmeticActivationRange<T>(params, _params.activation);
92 const bool need_broadcast = tflite::reference_ops::ProcessBroadcastShapes(
93 getTensorShape(input1()), getTensorShape(input2()), ¶ms);
97 tflite::reference_ops::BroadcastSubSlow(
98 params, getTensorShape(input1()), getTensorData<T>(input1()), getTensorShape(input2()),
99 getTensorData<T>(input2()), getTensorShape(output()), getTensorData<T>(output()));
103 tflite::reference_ops::Sub(params, getTensorShape(input1()), getTensorData<T>(input1()),
104 getTensorShape(input2()), getTensorData<T>(input2()),
105 getTensorShape(output()), getTensorData<T>(output()));
109 void Sub::evalQuantized() const
111 const auto input1_scale = static_cast<double>(input1()->scale());
112 const auto input2_scale = static_cast<double>(input2()->scale());
113 const auto output_scale = static_cast<double>(output()->scale());
115 const int left_shift = 20;
116 const double twice_max_input_scale = 2 * std::max(input1_scale, input2_scale);
117 const double real_input1_multiplier = input1_scale / twice_max_input_scale;
118 const double real_input2_multiplier = input2_scale / twice_max_input_scale;
119 const double real_output_multiplier = twice_max_input_scale / ((1 << left_shift) * output_scale);
121 int32_t input1_multiplier{}, input2_multiplier{}, output_multiplier{};
122 int input1_shift{}, input2_shift{}, output_shift{};
123 quantizeMultiplierSmallerThanOneExp(real_input1_multiplier, &input1_multiplier, &input1_shift);
124 quantizeMultiplierSmallerThanOneExp(real_input2_multiplier, &input2_multiplier, &input2_shift);
125 quantizeMultiplierSmallerThanOneExp(real_output_multiplier, &output_multiplier, &output_shift);
127 int32_t activation_min{};
128 int32_t activation_max{};
129 calculateActivationRangeQuantized(_params.activation, output(), &activation_min, &activation_max);
131 tflite::ArithmeticParams params{};
132 params.left_shift = left_shift;
133 // The kernel expects inputs' zero points to be negated.
134 params.input1_offset = -input1()->zero_point(); // Note the '-'.
135 params.input1_multiplier = input1_multiplier;
136 params.input1_shift = input1_shift;
137 params.input2_offset = -input2()->zero_point(); // Note the '-'.
138 params.input2_multiplier = input2_multiplier;
139 params.input2_shift = input2_shift;
140 params.output_offset = output()->zero_point();
141 params.output_multiplier = output_multiplier;
142 params.output_shift = output_shift;
143 params.quantized_activation_min = activation_min;
144 params.quantized_activation_max = activation_max;
146 const bool need_broadcast = tflite::reference_ops::ProcessBroadcastShapes(
147 getTensorShape(input1()), getTensorShape(input2()), ¶ms);
151 tflite::reference_ops::BroadcastQuantSubSlow(
152 params, getTensorShape(input1()), getTensorData<uint8_t>(input1()), getTensorShape(input2()),
153 getTensorData<uint8_t>(input2()), getTensorShape(output()), getTensorData<uint8_t>(output()));
157 tflite::reference_ops::Sub(params, getTensorShape(input1()), getTensorData<uint8_t>(input1()),
158 getTensorShape(input2()), getTensorData<uint8_t>(input2()),
159 getTensorShape(output()), getTensorData<uint8_t>(output()));
163 } // namespace kernels
164 } // namespace luci_interpreter